Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)

Implementation of Adaptive Neuro-Fuzzy Inference System Control on Pneumatic Solar Tracker

Authors
Baisrum Baisrum1, Budi Setiadi1, *, Sudrajat Sudrajat1, Varian Wijayakusuma1, Hilmi Ulhaq1, Rina Hikmawati1, Naufal Qamaruddin1, Sandi Hardiansyah1
1Department of Electrical Engineering, Politeknik Negeri Bandung, Indonesia
*Corresponding author. Email: budi.setiadi@polban.ac.id
Corresponding Author
Budi Setiadi
Available Online 23 November 2021.
DOI
10.2991/aer.k.211106.067How to use a DOI?
Keywords
Solar Tracker; Double-Acting Cylinder; Valve; ANFIS; UV Sensor
Abstract

The use of servo/stepper motor actuators in solar tracker systems requires additional gear components. These additional components affect the movement response output of the solar tracker system. This study research the accuracy, response output of a single-axis solar tracker system using pneumatic actuators and ultraviolet (UV) sensors. The type of pneumatic actuator used is a double-acting cylinder. The pneumatic actuator functions to move the solar tracker mechanically and are connected directly to the solar panel frame. Solar tracker moves from east to west automatically and vice versa. The movement of the solar tracker angle from 0° to 45° based on the combined reading of 2 UV sensors (UVx and UVy). The direction of movement of the tracker is regulated through 4 digital valves which are operated digitally. While the tracker speed is regulated through 1 proportional valve which is operated continuously. The opening and closing of the digital valve and the size of the proportional valve opening are regulated based on the results of the data processing and signal conditioning on the microcontroller. The data processing method uses an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS architecture uses a Sugeno fuzzy model with 2 inputs and 9 rules. Changes in the ANFIS output value are based on the combined reading feedback input from the UV sensor. System testing was carried out with a UV lamp. The experimental results show an average error of 1.6° for no-load conditions and 2.5° for loaded conditions in the east-west direction. The dynamic response of the system produces 2.08% overshoot, and 1.25% steady-state error.

Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)
Series
Advances in Engineering Research
Publication Date
23 November 2021
ISBN
978-94-6239-451-3
ISSN
2352-5401
DOI
10.2991/aer.k.211106.067How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Baisrum Baisrum
AU  - Budi Setiadi
AU  - Sudrajat Sudrajat
AU  - Varian Wijayakusuma
AU  - Hilmi Ulhaq
AU  - Rina Hikmawati
AU  - Naufal Qamaruddin
AU  - Sandi Hardiansyah
PY  - 2021
DA  - 2021/11/23
TI  - Implementation of Adaptive Neuro-Fuzzy Inference System Control on Pneumatic Solar Tracker
BT  - Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)
PB  - Atlantis Press
SP  - 422
EP  - 429
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.211106.067
DO  - 10.2991/aer.k.211106.067
ID  - Baisrum2021
ER  -